带标记的不完备双论域模糊概率粗糙集中近似集动态更新方法

当不完备双论域模糊概率粗糙集获取缺省值时,传统的静态算法更新近似集的时间效率较低,为了解决这个问题,对带标记不完备双论域模糊概率粗糙集的近似集动态更新方法进行了研究。首先,给出了带标记的不完备双论域信息系统的相关定义,运用矩阵提出了带标记的不完备双论域模糊概率粗糙集的模型,证明了其相关定理,给出了一种带标记的不完备双论域模糊概率粗糙集的近似集计算方法,并对其进行了讨论分析。其次,当不完备双论域模糊概率粗糙集获取缺省值时,给出了动态更新其近似集的相关定理,并进行了证明,进而设计了一种带标记的不完备双论域模糊概率粗糙集中近似集动态更新算法,并分析讨论了其算法复杂度。最后,在6个UCI数据集和3个人工数据集上进行仿真实验,实验结果表明,该动态更新算法提高了更新近似集的时间效率,并结合实例证明了该动态算法更新近似集时不影响结果的正确性,验证了该动态更新算法的有效性。

Label-based Approach for Dynamic Updating Approximations in Incomplete Fuzzy Probabilistic Rough Sets over Two Universes

When the missing values are obtained in incomplete fuzzy probabilistic rough sets over two universes,the time efficiency of the traditional static algorithm for updating approximations in incomplete fuzzy probabilistic rough sets over two universes is too low.To solve this problem,a label-based approach for dynamic updating approximations in incomplete fuzzy probabilistic rough sets over two universes isstudied.Firstly,some definitions of incomplete fuzzy probabilistic rough over two universes are given,then based on the matrix method,a label-based model of incomplete fuzzy probabilistic rough sets over two universes is proposed,and the related theorems are proved.After that,a label-based method for calculating approximations in incomplete fuzzy probabilistic rough sets over two universes is proposed and analyzed.Then,when the missing values are obtained in incomplete fuzzy probabilistic rough sets over two universes,the theorem for dynamic updating its approximations is proved,and a label-based algorithm for dynamic updating approximations in incomplete fuzzy probabilistic rough sets over two universes is designed and analyzed.Finally,the simulation experiments are conducted on six datasets from UCI and three man-made datasets.The experimental results show that the proposed dynamic updating algorithm can improve the time efficiency of updating approximations.Then an example shows that the dynamic algorithm does not affect the correctness of the results when updating approximations,which proves the validity of the proposed dynamic updating algorithm.